Despite proudly claiming in 2002 that "This page was generated entirely by computer algorithms without human editors. No humans were harmed or even used in the creation of this page", Google has rolled out a teaser for its new Editors' Pick section to its Google News site – featuring the selections of real human editors, outside of Google, selecting their special stories. Presently the current partners include The Washington Post, Newsday, Reuters, and Slate.

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(pictures from Google).Officially, Google says: "At Google, we run anywhere from 50 to 200 experiments at any given time on our websites all over the world. Right now, we are running a very small experiment in Google News called Editors' Picks. For this limited test, we're allowing a small set of publishers to promote their original news articles through the Editors' Picks section."

Even so, that means humans choosing news - not the normal Google News approach at all. So does this signal a change for how the site is run? Senior manager Chris Gaither of Google News was cautious in his response "I wouldn't read too much into this small experiment in terms of what it signals for the future".

Google has been upgrading its news site over the past few months, with an overhauled design (still to come to the UK site) which has taken into account user feedback, and Fast Flip, for quickly browsing through stories on multiple sites. (There's not much evidence that Fast Flip has taken off though: it may be consigned to the same box marked "not used by many" as Google Wave.)

The BBC has also recently redesigned its website for the first time since 2003, showing that the competition for news portals is hotting up.

Having the eye and ear for picking out a good news story is impossible to implement into an algorithm. The current Google News algorithm searches the internet to find newly-published stories on major sites and uses past trends to predict future hot stories. But the algorithm can't tell whether a single item is important, relevant or even interesting; that only emerges when others follow its lead. Adding the human element might help uncover those stories that are presently missed by the machines at the early stage.